Financial service providers collect countless pieces of information when they enter a new customer. But very few use them sensibly for up- and cross-selling. With AI support, it is very easy to create real value from customer data.
For financial services companies, onboarding new customers means one thing above all else: lots of paperwork. Proof of identity, address and income to comply with the applicable EU regulations for combating money laundering and terrorist financing as well as for BaFin-compliant customer verification are only the tip of the iceberg. From passports to driver’s licenses, electricity bills, bank statements and pay slips, the list of documents required is long, especially for complex issues. As a rule, the respective financial service provider scans and saves the submitted documents and links them to the customer data record in their own system using a reference number.
But despite Video-Ident and Co., the employees still have to do a lot of manual work. From the manual checking of the submitted information to the creation of cross-references to electronic documents, this not only means a lot of effort, but usually also the senseless waste of valuable information. Stored in a central database, the numerous details from the customer documents could represent enormous added value for those responsible for marketing. In other industries, such inputs are analyzed and valuable insights are gained from details such as age, region, income range and spending habits. In the scanned image files that are stored in financial service companies, however, only so-called “flat data” can be found – data without any meaningfulness whatsoever. Without the right context, this information is worthless and even costs money, according to IDC.
Gaining added value from documents
Smart technology enables financial services companies to make the most of data from customer onboarding and beyond. By identifying, extracting and classifying unstructured inputs, information is created with its associated context. Artificial intelligence (AI) and machine learning (ML) help in data extraction, as the system independently identifies and reads various fields – regardless of what type of document it is. The name and address of an energy bill can be recognized just as easily as the IBAN on an account statement. By entering various files in a wide variety of formats, the solution learns more and more bit by bit and thus becomes more and more intelligent. For example, it is also able to recognize, read and assign the necessary information for different financial products.
An important factor in this data processing is the context: AI and ML put every piece of information in its context and thus give it sustainable added value. From a simple name comparison between the account application and the submitted wage slip to the plausibility check of an application, so many manual tasks can be automated. And even more is possible: If a document is received for a mortgage application, this can not only be linked to the customer’s account details, but also to his credit balance, details of the property and insurance information of the property. By enriching the information with context, financial services companies transform “flat data” into a three-dimensional treasure trove of useful information.
Focus on the customer, positioning in competition
Financial service providers who use AI-based technology benefit from undreamt-of opportunities in the marketing environment. What Google, Facebook and Co. have been doing for some time and is no longer uncommon in retailing, also works for banks: The evaluation of customer data in order to get to know it even better and to make targeted offers. This understanding of customers harbors completely new sales opportunities that financial institutions are currently not using. In some cases, there is even a lack of assurance that a lender will recognize a mortgage applicant as an existing customer. Aside from creditworthiness based on account information, most banks are flying blind when it comes to their customers.
Reduced effort, saved time and increased efficiency are just the superficial advantages of AI-based technology for data extraction. Compliance also benefits when information is automatically processed and enriched with context in the onboarding process. In order to be able to use cross-selling options and to increase customer satisfaction through customized communication, financial service providers should increasingly rely on these innovative solutions. In view of the steadily growing competition from fintech startups, established banks have to act quickly in order not to lose touch.
The challenges of customer onboarding are obvious for financial service providers. Automation solutions should reduce the associated costs and make processes more efficient. But they can do a lot more. Data enriched with context opens up unimagined growth opportunities that must now be exploited.